Built In Jobs Scraper

Extract thousands of tech job listings from Built In — including salary ranges, company details, location data, required experience, benefits packages, and full job descriptions — without writing a single line of code.

What Does Built In Jobs Scraper Do?

Built In Jobs Scraper crawls builtin.com/jobs and extracts structured data from every job listing. For each position it retrieves:

• 🏢 Company information — name, profile URL, logo URL
• 💼 Job basics — title, employment type, direct-apply flag
• 📍 Location — city, state, country, GPS coordinates (lat/lng)
• 💰 Salary — min/max range, currency, period (hourly/annual/monthly)
• 🗓️ Dates — date posted, valid-through expiry
• 🏭 Industries — all tags assigned by Built In (e.g. Software, SaaS, FinTech)
• 🎁 Benefits — full list (401K, equity, dental, parental leave, etc.)
• 🎓 Requirements — months of experience, education level required
• 📝 Description — full plain-text job description (optional)

The scraper uses structured data (Schema.org JobPosting JSON-LD) embedded in each listing page, so the output is consistently typed and requires no brittle HTML parsing.

Who Is It For?

👩‍💼 Recruiters & Talent Sourcers

Monitor which companies are actively hiring for specific roles. Identify salary benchmarks by role and location. Build candidate outreach lists based on company size and industry.

📊 HR & Compensation Analysts

Pull salary data across hundreds of tech roles in minutes. Compare compensation by employment type, experience level, or geography. Track salary inflation trends over time with scheduled runs.

🚀 Job Seekers & Career Coaches

Aggregate listings from multiple search queries into a single spreadsheet. Filter by direct-apply, salary range, or required experience. Export to Airtable or Google Sheets for organised job hunting.

🤖 Data Scientists & Researchers

Build training datasets for NLP models (job description classification, salary prediction). Research tech hiring trends by industry, city, or technology stack.

🏢 Sales & GTM Teams

Identify companies that are scaling their engineering teams as a signal for SaaS outreach. Enrich prospect lists with real-time headcount-growth signals.

Why Use This Scraper?

• Schema.org data — uses structured JobPosting JSON-LD for typed, reliable fields
• No browser required — fast HTTP-only extraction (no Playwright overhead)
• Salary coverage — extracts min/max salary ranges where available
• Benefit lists — 20-50 benefits per listing, individually parsed
• GPS coordinates — latitude/longitude for mapping or geocoding workflows
• Paginated search — automatically crawls all pages for a search query

What Data Can You Extract?

Field	Type	Example
id	string	"4457551"
url	string	"https://builtin.com/job/software-engineer/4457551"
title	string	"Software Engineer"
companyName	string	"Oso"
companyUrl	string	"https://builtin.com/company/oso"
companyLogoUrl	string	"https://builtin.com/sites/..."
location	string	"New York, New York"
city	string	"New York"
state	string	"New York"
country	string	"USA"
latitude	number	40.7130466
longitude	number	-74.0072301
datePosted	string	"2026-05-05"
validThrough	string	"2026-06-04T00:04:37+00:00"
employmentType	string	"FULL_TIME"
salaryMin	number	100000
salaryMax	number	275000
salaryCurrency	string	"USD"
salaryPeriod	string	"YEAR"
industries	array	["Security","Software","IaaS"]
benefits	array	["401(K)","Company equity","Dental insurance",...]
directApply	boolean	false
experienceMonths	number	108 (= 9 years)
educationLevel	string	"Bachelor Degree"
description	string	Full plain-text job description

How Much Does It Cost to Scrape Built In Jobs?

Built In Jobs Scraper uses pay-per-result pricing — you only pay for jobs actually extracted. There is no charge for empty runs or failed requests.

Pricing tiers

Tier	Cost per job
Free (first 20 results/month)	$0.0023
Bronze (pay-as-you-go)	$0.002
Silver	$0.00156
Gold	$0.0012
Platinum	$0.0008
Diamond	$0.00056

Example costs

Scenario	Jobs	Estimated cost
Quick market research	50	~$0.10
Weekly job feed	500	~$1.00
Bulk salary analysis	2,000	~$4.00
Full index snapshot	10,000	~$20.00

Free plan estimate: Apify's $49/mo plan includes ~$5 in compute credits, enough for approximately 2,500 job listings per month at the Bronze rate.

How to Scrape Built In Jobs — Step by Step

1. Open the actor on the Apify platform and click Try for free.
2. Set a Start URL — paste any Built In jobs page URL (e.g. https://builtin.com/jobs?search=machine+learning). Leave it as the default https://builtin.com/jobs to scrape all recent postings.
3. (Optional) Enter Keywords — type a job title or skill keyword if you prefer not to construct the URL manually.
4. Set Max Jobs — enter how many listings you want (e.g. 200).
5. Toggle Include Description — enable to get the full job description text.
6. Click Start — the scraper runs and populates your dataset in real time.
7. Export — download results as JSON, CSV, Excel, or connect to Zapier / Make.

Input Parameters

Parameter	Type	Default	Description
startUrls	array	[{"url":"https://builtin.com/jobs"}]	Built In jobs page URLs to crawl with automatic pagination
keywords	string	—	Job title keyword search (used when Start URLs is empty)
maxJobs	integer	100	Maximum number of job listings to extract
includeDescription	boolean	true	Include full plain-text job description in output
maxRequestRetries	integer	3	Retry limit for failed HTTP requests

Supported start URL formats

https://builtin.com/jobs                          All jobs
https://builtin.com/jobs?search=data+scientist    Keyword search
https://builtin.com/remote-jobs                   Remote only
https://builtin.com/jobs/chicago                  City filter
https://builtin.com/jobs/san-francisco            City filter

Output Example

{
  "id": "4457551",
  "url": "https://builtin.com/job/software-engineer/4457551",
  "title": "Software Engineer",
  "companyName": "Oso",
  "companyUrl": "https://builtin.com/company/oso",
  "companyLogoUrl": "https://builtin.com/sites/www.builtin.com/files/2024-12/Oso.jpeg",
  "location": "New York, New York",
  "city": "New York",
  "state": "New York",
  "country": "USA",
  "latitude": 40.7130466,
  "longitude": -74.0072301,
  "datePosted": "2026-05-05",
  "validThrough": "2026-06-04T00:04:37+00:00",
  "employmentType": "FULL_TIME",
  "salaryMin": 100000,
  "salaryMax": 275000,
  "salaryCurrency": "USD",
  "salaryPeriod": "YEAR",
  "industries": ["Security", "Software", "Infrastructure as a Service (IaaS)"],
  "benefits": ["401(K)", "Company equity", "Dental insurance", "Health insurance", "Unlimited vacation policy"],
  "directApply": false,
  "experienceMonths": 108,
  "educationLevel": "Bachelor Degree",
  "description": "Old problem, new $25B+ market\n\nCompanies like AWS, Stripe, and Twilio..."
}

Tips & Best Practices

• 🔍 Use specific search URLs for targeted scraping — builtin.com/jobs?search=react+developer returns more relevant results than scraping all jobs and filtering afterward.
• 📅 Schedule weekly runs to maintain a fresh jobs feed — Built In listings expire after ~30 days so weekly is sufficient for most use cases.
• 💡 Disable descriptions when you only need job metadata — set includeDescription: false to halve response sizes and speed up large runs.
• 🗺️ Use GPS coordinates for geospatial analysis — the lat/lng fields are directly usable in mapping tools like Mapbox, Google Maps, or Tableau.
• 📊 Filter by salaryMin in downstream tools — not all jobs list salary, but those that do are the most useful for compensation benchmarking.
• 🔄 Combine multiple start URLs — add builtin.com/jobs?search=backend and builtin.com/jobs?search=frontend as separate start URLs in one run to collect both in parallel.
• ⚡ Use maxJobs to cap spend on exploratory runs — start with 20-50 jobs to validate your search URL before scaling to thousands.

Integrations

📊 Export to Google Sheets for salary tracking

Use Apify's Google Sheets integration to push job data directly into a spreadsheet. Set up a scheduled run every Monday and your salary tracker auto-updates with the latest listings.

🔔 Slack alerts for new jobs at target companies

Combine with Apify's webhook notifications to receive a Slack message whenever a new job appears from a company on your watchlist.

🔗 Enrich LinkedIn Sales Navigator leads

Export companies from job listings → import into LinkedIn Sales Navigator → reach hiring managers the week they posted a role.

🗂️ Airtable recruiting database

Connect via Zapier: new job → filter by salary ≥ $X and required skills → create Airtable record. Build your own ATS with zero coding.

📧 Email digest with Make (formerly Integromat)

Trigger a Make scenario on run completion → filter jobs by your criteria → send a formatted daily email with the best matches.

API Usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('automation-lab/builtin-jobs-scraper').call({
    startUrls: [{ url: 'https://builtin.com/jobs?search=software+engineer' }],
    maxJobs: 100,
    includeDescription: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Scraped ${items.length} jobs`);
items.forEach(job => {
    console.log(`${job.title} @ ${job.companyName} — ${job.location}`);
    if (job.salaryMin) console.log(`  Salary: $${job.salaryMin}–$${job.salaryMax} ${job.salaryPeriod}`);
});

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("automation-lab/builtin-jobs-scraper").call(
    run_input={
        "startUrls": [{"url": "https://builtin.com/jobs?search=data+scientist"}],
        "maxJobs": 200,
        "includeDescription": False,
    }
)

dataset_items = client.dataset(run["defaultDatasetId"]).list_items().items
for job in dataset_items:
    salary = f"${job.get('salaryMin')}–${job.get('salaryMax')} {job.get('salaryPeriod')}" \
             if job.get('salaryMin') else "Not listed"
    print(f"{job['title']} @ {job['companyName']} | {job['location']} | {salary}")

cURL

# Start the scraper
curl -X POST "https://api.apify.com/v2/acts/automation-lab~builtin-jobs-scraper/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "startUrls": [{"url": "https://builtin.com/jobs?search=backend+engineer"}],
    "maxJobs": 50,
    "includeDescription": true
  }'

# Get results (replace RUN_ID with the ID from the response above)
curl "https://api.apify.com/v2/datasets/RUN_ID/items?token=YOUR_API_TOKEN&format=json"

Use With Claude and Other AI Assistants (MCP)

Built In Jobs Scraper is available as an MCP (Model Context Protocol) tool, letting AI assistants like Claude run the scraper and analyse results in one conversation.

Claude Code (terminal)

$claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/builtin-jobs-scraper"

Claude Desktop / Cursor / VS Code

Add to your MCP config (claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "apify": {
      "type": "http",
      "url": "https://mcp.apify.com?tools=automation-lab/builtin-jobs-scraper",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Example Claude prompts

"Scrape 200 software engineer jobs from Built In and find the top 10 companies hiring the most. Show their average salary ranges."

"Pull 100 remote Python jobs from builtin.com, then list all unique benefits offered and rank them by frequency."

"Get all product manager roles posted in the last week on Built In and create a comparison table sorted by salary."

Legality — Is Scraping Built In Legal?

Built In's publicly accessible job listings contain data that companies have intentionally published for public viewing. Scraping publicly available job data for personal research, market analysis, and non-commercial purposes is generally considered lawful in most jurisdictions.

The built-in.com robots.txt permits crawling of job listing pages. This scraper:

• Does not require login or bypass any access controls
• Respects rate limits with automatic delays between requests
• Only collects data that is publicly visible to any visitor

You are responsible for ensuring your use of the extracted data complies with applicable laws, Built In's Terms of Service, and data privacy regulations (GDPR, CCPA) in your jurisdiction. Do not use extracted personal data (such as contact information) for unsolicited outreach.

FAQ — Frequently Asked Questions

How many jobs can I scrape in one run? There is no hard limit. The scraper handles pagination automatically. Practically, builtin.com has ~10,000–50,000 active listings at any time. For very large runs (>5,000 jobs), consider splitting by search query to manage memory and cost.

Does it scrape all cities or just one? The default builtin.com/jobs URL covers all cities. Use city-specific URLs like builtin.com/jobs/chicago or builtin.com/jobs/new-york to restrict to a single metro area.

Why are some salary fields null? Not all companies list salary ranges. Built In encourages it but doesn't require it. Roughly 40–60% of listings include salary data.

Can I filter by remote, hybrid, or on-site? Yes — construct a filtered URL on Built In's website (use the "Remote" dropdown), then copy that URL as your start URL. The scraper will respect the filter.

The scraper returned fewer jobs than expected — why? Built In paginates results at 24–25 per page. If your maxJobs is less than the total matching results, the scraper stops early (by design). Also, some listing pages may lack JSON-LD data and are skipped with a warning in the log.

I'm getting 403 errors on some pages. How do I fix it? Built In occasionally rate-limits high-frequency requests. Reduce the run frequency or lower maxJobs. The scraper uses automatic retries (maxRequestRetries), which resolves transient blocks automatically.

Related Scrapers

Looking for job data from other platforms?

• Glassdoor Jobs Scraper — salary reviews + job listings from Glassdoor
• LinkedIn Jobs Scraper — LinkedIn job postings with company details
• Indeed Jobs Scraper — Indeed listings with apply links
• Wellfound Scraper — AngelList/Wellfound startup jobs

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